Which type of model is utilized to help managers use historical data to predict future conditions and sales figures resulting from these conditions?

The type of model that managers utilize to predict future conditions and sales figures based on historical data is called forecasting. Forecasting models analyze trends and patterns within past data to generate estimates about future outcomes. They are particularly important in business for planning purposes, as they enable managers to make informed decisions regarding inventory, staffing, budget allocation, and overall strategy.

Forecasting can take many forms, including time series analysis, causal models, and qualitative approaches, and it often leverages statistical methods to quantify uncertainties and variability in predictions. By employing these models, organizations are better positioned to anticipate market demands and respond proactively to changing conditions.

In contrast, the other types of models mentioned serve different purposes. Optimization models focus on finding the best solutions within given constraints, often in resource allocation scenarios. Sensitivity analysis examines how changes in certain variables affect outcomes, helping to understand the robustness of a decision. Statistical models are broader and may encompass a variety of tools used for data analysis, but they do not exclusively focus on the predictive modeling aspect as forecasting does. Therefore, forecasting is specifically designed for the task of predicting future sales and conditions based on historical data.